Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/awslabs/agent-plugins/directory-managementnpx skills add awslabs/agent-plugins --skill directory-managementgit clone --depth 1 https://github.com/awslabs/agent-pluginsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00062 | $0.00379 |
| Opus 5 | $0.00031 | $0.00189 |
| Sonnet 5 | $0.00012 | $0.00076 |
| Haiku 4.5 | $0.00006 | $0.00038 |
Grade A, and why
directory-management scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Directory Management
Project Setup
Before any work begins, resolve the project name:
- If the project name is already known from conversation context, use it.
- Otherwise, scan for existing
*/PLAN.mdfiles in the current directory. If found, ask the user if they are resuming an existing project and load thatPLAN.mdinto context. - If no existing projects are found, recommend a ≤64-char lowercase slug based on what you know from the conversation (only
[a-z0-9-]), or ask directly if there isn't enough context. Present the recommended name and wait for user confirmation.
Once project name is resolved:
- Create and/or use the
<experiment-name>/directory using the confirmed name for storing all the artifacts
Directory Structure
When working with the agent, all generated files are organized under an project directory.
<project-name>/
├── specs/
│ ├── PLAN.md # Your customization plan
├── scripts/ # Generated Python scripts
│ ├── <project-name>_transform_fn.py
├── notebooks/ # Generated Jupyter notebooks
│ ├── <project-name>.ipynb
├── manifests/ # Machine-readable outputs (JSON)
└── agent_memory/ # Session persistence (git-ignored)
└── session-notes.md # Progress, artifacts, next steps
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 38 lines · 62 tokens per session scan A 19c160fb3f80
directory-management is a skill published in the GitHub repository awslabs/agent-plugins (876 stars, last pushed 6d ago), licensed Apache-2.0. It adds 62 tokens to every session and 379 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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